activity
20182021
most citedCross-modal Attention for MRI and Ultrasound Volume Registration

6 citations · 7 across the 4 of their papers we have counts for

collaborators

6 papers

eess.IV2021

End-to-end Ultrasound Frame to Volume Registration

Hengtao Guo, Xuanang Xu, Sheng Xu +2

Fusing intra-operative 2D transrectal ultrasound (TRUS) image with pre-operative 3D magnetic resonance (MR) volume to guide prostate biopsy can significantly increase the yield. Ho…

cs.CV20216 cited

Cross-modal Attention for MRI and Ultrasound Volume Registration

Xinrui Song, Hengtao Guo, Xuanang Xu +6

Prostate cancer biopsy benefits from accurate fusion of transrectal ultrasound (TRUS) and magnetic resonance (MR) images. In the past few years, convolutional neural networks (CNNs…

cs.CV2020

Transducer Adaptive Ultrasound Volume Reconstruction

Hengtao Guo, Sheng Xu, Bradford J. Wood +1

Reconstructed 3D ultrasound volume provides more context information compared to a sequence of 2D scanning frames, which is desirable for various clinical applications such as ultr…

cs.CV20201 cited

Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learning

Hengtao Guo, Sheng Xu, Bradford Wood +1

Transrectal ultrasound (US) is the most commonly used imaging modality to guide prostate biopsy and its 3D volume provides even richer context information. Current methods for 3D v…

cs.CV2019

Knowledge-based Analysis for Mortality Prediction from CT Images

Hengtao Guo, Uwe Kruger, Ge Wang +2

Recent studies have highlighted the high correlation between cardiovascular diseases (CVD) and lung cancer, and both are associated with significant morbidity and mortality. Low-Do…

cs.CV2018

Hybrid deep neural networks for all-cause Mortality Prediction from LDCT Images

Pingkun Yan, Hengtao Guo, Ge Wang +2

Known for its high morbidity and mortality rates, lung cancer poses a significant threat to human health and well-being. However, the same population is also at high risk for other…